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Artificial Intelligence (AI) in Networking Market: Global Forecast to 2032 | AI Workloads Push Networks to Run Themselves, Fueling a $21 Billion Market

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CSCO Cisco is listed as a leading participant in the AI in Network market, with specific mention of its 'Self-Defending Network for AI-Driven Security'. This indicates a positive involvement and strategy in the growing AI networking space. HPE HPE is listed as a leading participant in the AI in Network market. The article does not provide specific details on HPE's performance or strategy within this market, only its inclusion as a key player. NOK Nokia is identified as a leading participant in the AI in Network market. The article specifically mentions 'Nokia AI-Powered Autonomous RAN Operations for STC', highlighting its active role and solutions in AI-driven network operations. ERIC Ericsson is listed as a leading participant in the AI in Network market. The article highlights its involvement with 'Ericsson AI-Driven Network Optimization for AT&T', indicating a positive contribution to AI in networking solutions. NVDA NVIDIA is listed as a leading participant in the AI in Network market. The article emphasizes the need for high-bandwidth, low-latency infrastructure for AI workloads, which is NVIDIA's core strength, especially with GPUs. EXTR Extreme Networks is listed as a leading participant in the AI in Network market. The article does not provide specific details on its performance or strategy within this market, only its inclusion as a key player. AVGO Broadcom is listed as a leading participant in the AI in Network market. The article does not provide specific details on its performance or strategy within this market, only its inclusion as a key player. IBM IBM is listed as a leading participant in the AI in Network market. The article does not provide specific details on its performance or strategy within this market, only its inclusion as a key player. DELL Dell Technologies is listed as a leading participant in the AI in Network market. The article does not provide specific details on its performance or strategy within this market, only its inclusion as a key player. CIEN Ciena is listed as a leading participant in the AI in Network market. The article does not provide specific details on its performance or strategy within this market, only its inclusion as a key player. DT Dynatrace is listed as a leading participant in the AI in Network market. The article does not provide specific details on its performance or strategy within this market, only its inclusion as a key player. VIAV VIAVI Solutions is listed as a leading participant in the AI in Network market. The article does not provide specific details on its performance or strategy within this market, only its inclusion as a key player.

Artificial Intelligence (AI) in Networking Market: Global Forecast to 2032 | AI Workloads Push Networks to Run Themselves, Fueling a $21 Billion Market Dublin, Oct. 21, 2026 (GLOBE NEWSWIRE) -- "AI in Network Market: Global Forecast to 2032" has been added to ResearchAndMarkets.com's offering.

AI in Network Market to Reach USD 21.52 Billion by 2032 as Automation, 5G and Cloud Adoption Accelerate

The AI in network market is projected to grow from USD 8.38 billion in 2026 to USD 21.52 billion by 2032, registering a CAGR of 17.0%. Market expansion is being driven by the growing adoption of AI-powered network automation, 5G, edge computing, cloud infrastructure and IoT across telecom operators, enterprises, data centers and public-sector organizations.

Organizations are integrating AI into network operations to support real-time network optimization, predictive maintenance, anomaly detection, automated troubleshooting and enhanced cybersecurity. These capabilities help improve network performance, reduce downtime, optimize resource utilization and lower operational costs. Rising investment in digital infrastructure, combined with increasing demand for reliable, secure and low-latency connectivity, is expected to accelerate the transition toward autonomous and intelligent networks.

Data center networks to account for the largest market share

By network type, data center networks are expected to hold the largest share of the AI in network market during the forecast period. Growth is supported by the rapid deployment of AI workloads, cloud computing, generative AI, machine learning and high-performance computing across enterprises and hyperscalers.

These workloads require high-bandwidth, low-latency and scalable infrastructure capable of transferring large datasets among GPUs, servers and storage systems. AI-driven networking solutions enable data centers to automate network operations, optimize traffic management, identify performance issues and improve resource utilization. Continued investment in next-generation data centers is expected to sustain demand for AI-enabled network monitoring, automation, security and performance optimization.

Cloud networks to register the fastest growth

The cloud networks segment is forecast to record the highest growth rate as enterprises expand cloud migration initiatives and adopt hybrid and multicloud architectures. Increasing infrastructure complexity is creating demand for AI-enabled solutions that provide real-time visibility, automated configuration, intelligent traffic management and predictive performance optimization.

AI-driven cloud networking supports anomaly detection, resource optimization and operational automation across cloud environments, data centers, branch locations and edge infrastructure. The expansion of cloud-native applications and the need for secure, resilient and scalable connectivity will further strengthen demand throughout the forecast period.

Asia Pacific positioned as the fastest-growing regional market

Asia Pacific is expected to register the highest growth rate in the AI in network market. China, India, Japan, South Korea and Australia are investing significantly in 5G infrastructure, data centers, cloud networks and advanced telecommunications systems to support increasing data traffic and connected devices.

Telecom operators and enterprises across the region are deploying AI-powered solutions for predictive maintenance, traffic management, anomaly detection, network optimization and automated operations. The proliferation of IoT, edge computing and 5G is generating substantial volumes of network data, expanding opportunities for AI-driven analytics. Government initiatives supporting digitalization, smart infrastructure and next-generation connectivity are also contributing to regional market growth.

Market opportunities, restraints and challenges

The report identifies the proliferation of AI agents, increasing DNS/IP demand, changing traffic patterns from AI workloads and growing interest in autonomous, self-optimizing and closed-loop networks as important market drivers. Opportunities include the adoption of generative and agentic AI for autonomous network operations, along with the expansion of AI-powered network management across cloud, edge and 5G environments.

Market growth may be constrained by limited explainability and trust in AI-driven network decisions, as well as the complexity of integrating AI with legacy network infrastructure. Additional challenges include maintaining high-quality, reliable and secure network data for AI models while addressing cybersecurity, data governance and operational risks.

Competitive landscape and research coverage

The report evaluates the market by offering, network type, end user and region. It also provides competitive analysis, company profiles, recent developments, product and business strategies, research and development activity, new launches, investment trends and opportunities in underserved markets.

Leading participants include Cisco, HPE, Nokia, Ericsson, Huawei, Arista Networks, NVIDIA, Extreme Networks, Broadcom, IBM, Fujitsu, Dell Technologies, Ciena, NEC, Forward Networks, BlueCat Networks, A10 Networks, ScienceLogic, Versa Networks, Dynatrace, Infoblox, EfficientIP, Riverbed, NETSCOUT, SolarWinds, NetBrain, ManageEngine, VIAVI Solutions, Selector, Aviz Networks, Nile, NetBox Labs, Celona, Shabodi and A5G Networks.

Breakdown of primary research participants

The report provides market leaders and new entrants with revenue estimates, segment-level growth projections and analysis of key drivers, restraints, opportunities and challenges. These insights can help stakeholders assess the competitive environment, refine go-to-market strategies, identify product development priorities and evaluate growth opportunities across global AI networking markets.

Key Attributes:

Key Topics Covered:

1 INTRODUCTION

1.1 STUDY OBJECTIVES

1.2 MARKET DEFINITION

1.3 MARKET SCOPE

1.3.1 MARKET SEGMENTATION AND REGIONAL SCOPE

1.3.2 INCLUSIONS AND EXCLUSIONS

1.4 YEARS CONSIDERED

1.5 CURRENCY CONSIDERED

1.6 STAKEHOLDERS

2 EXECUTIVE SUMMARY

2.1 MARKET HIGHLIGHTS AND KEY INSIGHTS

2.2 KEY MARKET PARTICIPANTS: MAPPING OF STRATEGIC DEVELOPMENTS

2.3 DISRUPTIVE TRENDS IN AI IN NETWORK MARKET

2.4 HIGH-GROWTH SEGMENTS

2.5 REGIONAL SNAPSHOT: MARKET SIZE, GROWTH RATE, AND FORECAST

3 PREMIUM INSIGHTS

3.1 ATTRACTIVE OPPORTUNITIES FOR PLAYERS IN AI IN NETWORK MARKET

3.2 AI IN NETWORK MARKET, BY SERVICE AND REGION

3.3 AI IN NETWORK MARKET, BY OFFERING

3.4 AI IN NETWORK MARKET, BY END USER

4 MARKET OVERVIEW AND INDUSTRY TRENDS

4.1 INTRODUCTION

4.2 MARKET DYNAMICS

4.2.1 DRIVERS

4.2.1.1 AI agent proliferation increasing DNS/IP demand

4.2.1.2 Growing adoption of AI, generative AI, and AI agents for network operations and automation

4.2.1.3 Rising complexity and changing traffic patterns driven by AI workloads

4.2.1.4 Increasing focus on autonomous, self-optimizing, and closed-loop networks

4.2.2 RESTRAINTS

4.2.2.1 Lack of explainability and trust in AI-driven network decisions

4.2.2.2 High complexity of integrating AI with legacy network infrastructure

4.2.3 OPPORTUNITIES

4.2.3.1 Expansion of autonomous and intent-based networking enabled by AI

4.2.3.2 Expansion of AI-powered network management across cloud, edge, and 5G environments

4.2.4 CHALLENGES

4.2.4.1 Ensuring high-quality, reliable, and secure network data for AI models

4.2.4.2 Managing cybersecurity, data governance, and operational risks

4.3 INTERCONNECTED MARKETS AND CROSS-SECTOR OPPORTUNITIES

4.3.1 CLOUD COMPUTING AND DATA CENTER MARKET

4.3.2 INTERNET OF THINGS (IOT) MARKET

4.3.3 CYBERSECURITY MARKET

4.3.4 TELECOMMUNICATIONS AND 5G MARKET

4.3.5 HEALTHCARE AND LIFE SCIENCES

4.3.6 MANUFACTURING AND INDUSTRIAL AUTOMATION

4.3.7 TRANSPORTATION AND SMART MOBILITY

4.3.8 ENERGY AND UTILITIES

4.3.9 RETAIL AND SMART ENTERPRISE

4.4 STRATEGIC MOVES BY TIER-1/2/3 PLAYERS

5 INDUSTRY TRENDS

5.1 PORTER'S FIVE FORCES ANALYSIS

5.1.1 THREAT OF NEW ENTRANTS

5.1.2 THREAT OF SUBSTITUTES

5.1.3 BARGAINING POWER OF SUPPLIERS

5.1.4 BARGAINING POWER OF BUYERS

5.1.5 INTENSITY OF COMPETITIVE RIVALRY

5.2 MACROECONOMICS INDICATORS

5.2.1 INTRODUCTION

5.2.2 GDP TRENDS AND FORECAST

5.2.3 TRENDS IN TELECOMMUNICATIONS INDUSTRY

5.2.4 TRENDS IN DATA CENTER & CLOUD INFRASTRUCTURE INDUSTRY

5.3 SUPPLY CHAIN ANALYSIS

5.4 ECOSYSTEM ANALYSIS

5.5 PRICING ANALYSIS

5.5.1 AVERAGE SELLING PRICE OF AI-ENABLED NETWORK MANAGEMENT PLATFORMS, BY KEY PLAYERS

5.5.2 INDICATIVE PRICING ANALYSIS OF KEY PLAYERS, BY SOLUTION, 2025

5.6 KEY CONFERENCES AND EVENTS, 2026-2027

5.7 TRENDS/DISRUPTIONS IMPACTING CUSTOMER BUSINESS

5.8 INVESTMENT AND FUNDING SCENARIO

5.9 CASE STUDY ANALYSIS

5.9.1 CISCO'S SELF-DEFENDING NETWORK FOR AI-DRIVEN SECURITY

5.9.2 NOKIA AI-POWERED AUTONOMOUS RAN OPERATIONS FOR STC

5.9.3 ERICSSON AI-DRIVEN NETWORK OPTIMIZATION FOR AT&T

5.9.4 SHABODI ENABLES AI-DRIVEN COGNITIVE FACTORY FOR GLOBAL MANUFACTURER

5.9.5 AVIZ NETWORKS BUILDS AI-READY NETWORK FOR GLOBAL E-COMMERCE

5.10 IMPACT OF 2025 US TARIFF - AI IN NETWORK MARKET

5.10.1 INTRODUCTION

5.10.2 KEY TARIFF RATES

5.10.3 PRICE IMPACT ANALYSIS

5.10.3.1 Strategic shifts and emerging trends

5.10.4 IMPACT ON COUNTRIES/REGIONS

5.10.4.1 US

5.10.4.2 Europe

5.10.4.3 Asia Pacific

5.10.5 IMPACT ON END-USER INDUSTRIES

5.10.5.1 Enterprises

5.10.5.2 Telecom & communication service providers

5.10.5.3 Government & defense

6 TECHNOLOGICAL ADVANCEMENTS, AI-DRIVEN IMPACT, PATENTS, INNOVATIONS, AND FUTURE APPLICATIONS

6.1 KEY EMERGING TECHNOLOGIES

6.1.1 ARTIFICIAL INTELLIGENCE (AI)

6.1.2 MACHINE LEARNING (ML)

6.1.3 GENERATIVE AI (GEN AI) AND LARGE LANGUAGE MODELS (LLMS)

6.1.4 AGENTIC AI

6.1.5 AI-NATIVE NETWORK AUTOMATION AND AUTONOMOUS NETWORKING

6.1.6 COMPLEMENTARY TECHNOLOGIES

6.1.6.1 Edge computing

6.1.6.2 Cloud computing

6.1.6.3 Network telemetry and observability

6.1.6.4 5G and 6G connectivity

6.1.7 ADJACENT TECHNOLOGIES

6.1.7.1 Digital twins

6.1.7.2 Internet of Things (IoT)

6.1.7.3 Intent-based networking (IBN)

6.1.7.4 Zero-touch network management

6.2 TECHNOLOGY/PRODUCT ROADMAP

6.2.1 SHORT-TERM ROADMAP (2026-2027)

6.2.2 MID-TERM ROADMAP (2028-2029)

6.2.3 LONG-TERM ROADMAP (2030-2032)

6.3 PATENT ANALYSIS

6.4 IMPACT OF AI/GEN AI ON AI IN NETWORK MARKET

6.4.1 TOP USE CASES AND MARKET POTENTIAL

6.4.2 BEST PRACTICES IN AI IN NETWORK PROCESS

6.4.3 CASE STUDIES OF AI IMPLEMENTATION IN AI IN NETWORK MARKET

6.4.4 INTERCONNECTED ADJACENT ECOSYSTEM AND IMPACT ON MARKET PLAYERS

6.4.5 CLIENTS' READINESS TO ADOPT GENERATIVE AI IN AI IN NETWORK

7 REGULATORY LANDSCAPE

7.1 REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS

7.2 INDUSTRY STANDARDS

8 CUSTOMER LANDSCAPE AND BUYING BEHAVIOR

8.1 DECISION-MAKING PROCESS

8.2 KEY STAKEHOLDERS INVOLVED IN BUYING PROCESS AND THEIR EVALUATION CRITERIA

8.2.1 KEY STAKEHOLDERS IN BUYING PROCESS

8.2.2 BUYING CRITERIA

8.3 ADOPTION BARRIERS AND INTERNAL CHALLENGES

8.4 UNMET NEEDS FROM VARIOUS END-USE INDUSTRIES

9 AI IN NETWORK MARKET, BY OFFERING

9.1 INTRODUCTION

9.1.1 OFFERING: AI IN NETWORK MARKET DRIVERS

9.2 SOLUTIONS

9.2.1 ENABLING INTELLIGENT, AUTOMATED, AND AUTONOMOUS NETWORK OPERATIONS

9.2.2 AI-DRIVEN NETWORK MANAGEMENT

9.2.2.1 Network monitoring & management

9.2.2.2 Network observability

9.2.2.3 DDI

9.2.2.4 Fault management

9.2.2.5 Performance management

9.2.3 AI-DRIVEN NETWORK OPTIMIZATION

9.2.3.1 Traffic optimization

9.2.3.2 Capacity optimization

9.2.3.3 Predictive performance analytics

9.2.3.4 Observability-driven optimization

9.2.4 AI-DRIVEN NETWORK SECURITY

9.2.4.1 Network policy & risk analytics

9.2.4.2 DNS security

9.2.4.3 Anomaly detection

9.2.4.4 Threat detection & response

9.2.5 AI-DRIVEN NETWORK AUTOMATION

9.2.5.1 Configuration automation

9.2.5.2 Provisioning automation

9.2.5.3 Policy automation

9.2.5.4 Closed-loop automation

9.2.5.5 DDI automation

9.2.6 AI-DRIVEN NETWORK ORCHESTRATION

9.2.6.1 Multi-domain network orchestration

9.2.6.2 Service orchestration

9.2.6.3 Intent-based orchestration

9.2.6.4 Autonomous network orchestration

9.2.7 AI-DRIVEN NETWORK PLANNING & DESIGN

9.2.7.1 Capacity planning & forecasting

9.2.7.2 Network architecture & topology design

9.2.7.3 Network simulation & digital twin

9.2.8 OTHER SOLUTIONS

9.3 SERVICES

9.3.1 ENABLING AI-DRIVEN NETWORK TRANSFORMATION AND AUTONOMOUS OPERATIONS

9.3.2 PROFESSIONAL SERVICES

9.3.2.1 Consulting & advisory

9.3.2.2 Integration & deployment

9.3.2.3 Support & maintenance

9.3.3 MANAGED SERVICES

10 AI IN NETWORK MARKET, BY NETWORK TYPE

10.1 INTRODUCTION

10.1.1 NETWORK TYPE: AI IN NETWORK MARKET DRIVERS

10.2 DATA CENTER NETWORKS

10.2.1 AI-DRIVEN OPTIMIZATION OF HIGH-PERFORMANCE INFRASTRUCTURE

10.3 CLOUD NETWORKS

10.3.1 AI-ENABLED MANAGEMENT OF DISTRIBUTED CLOUD INFRASTRUCTURE

10.4 WIRELESS NETWORKS

10.4.1 AI-DRIVEN OPTIMIZATION OF NEXT-GENERATION CONNECTIVITY

10.5 SOFTWARE-DEFINED WIDE AREA NETWORKS (SD-WAN)

10.5.1 AI-ENABLED INTELLIGENT TRAFFIC MANAGEMENT

10.6 CAMPUS NETWORKS

10.6.1 AI-DRIVEN NETWORK AUTOMATION AND PERFORMANCE MANAGEMENT

10.7 OTHER NETWORK TYPES

11 AI IN NETWORK MARKET, BY END USER

11.1 INTRODUCTION

11.1.1 END USER: AI IN NETWORK MARKET DRIVERS

11.2 SERVICE PROVIDERS

11.2.1 INCREASING ADOPTION OF AI TO ENABLE AUTONOMOUS AND INTELLIGENT NETWORK OPERATIONS

11.3 ENTERPRISES

11.3.1 GROWING DEPLOYMENT OF AI-DRIVEN NETWORKS TO ENHANCE OPERATIONAL EFFICIENCY, SECURITY, AND CONNECTIVITY

11.3.2 BFSI

11.3.3 HEALTHCARE

11.3.4 RETAIL & E-COMMERCE

11.3.5 MANUFACTURING

11.3.6 GOVERNMENT & DEFENSE

11.3.7 ENERGY & UTILITIES

11.3.8 OTHER ENTERPRISES

12 AI IN NETWORK MARKET, BY REGION

12.1 INTRODUCTION

12.2 NORTH AMERICA

12.2.1 NORTH AMERICA: AI IN NETWORK MARKET DRIVERS

12.2.2 US

12.2.2.1 Strong AI infrastructure investments driving autonomous and AI-native networks

12.2.3 CANADA

12.2.3.1 Sovereign AI infrastructure and 5G modernization supporting intelligent networks

12.3 EUROPE

12.3.1 EUROPE: AI IN NETWORK MARKET DRIVERS

12.3.2 UK

12.3.2.1 AI-enabled network automation and growing demand for intelligent connectivity

12.3.3 GERMANY

12.3.3.1 Industry 4.0 and autonomous network operations driving AI adoption

12.3.4 ITALY

12.3.4.1 5G modernization and industrial digitalization accelerating AI in networks

12.3.5 FRANCE

12.3.5.1 AI-native communications and digital sovereignty strengthening network intelligence

12.3.6 REST OF EUROPE

12.4 ASIA PACIFIC

12.4.1 ASIA PACIFIC: AI IN NETWORK MARKET DRIVERS

12.4.2 CHINA

12.4.2.1 Government-led AI integration and extensive 5G infrastructure driving autonomous networks

12.4.3 INDIA

12.4.3.1 Rapid 5G expansion and high data consumption fueling AI-driven network optimization

12.4.4 JAPAN

12.4.4.1 Advanced telecom infrastructure and AI automation supporting next-generation networks

12.4.5 REST OF ASIA PACIFIC

12.5 MIDDLE EAST & AFRICA

12.5.1 MIDDLE EAST & AFRICA: AI IN NETWORK MARKET DRIVERS

12.5.2 UAE

12.5.2.1 Sovereign AI and advanced 5G infrastructure accelerating AI-native network development

12.5.3 KSA

12.5.3.1 Vision 2030 and AI infrastructure investments driving intelligent connectivity

12.5.4 SOUTH AFRICA

12.5.4.1 5G Expansion and Digital Infrastructure Investment Supporting AI-Enabled Networks

12.5.5 REST OF MIDDLE EAST & AFRICA

12.6 LATIN AMERICA

12.6.1 LATIN AMERICA: AI IN NETWORK MARKET DRIVERS

12.6.2 BRAZIL

12.6.2.1 5G densification and operator automation driving adoption of AI in network

12.6.3 MEXICO

12.6.3.1 5G expansion and industrial digitalization supporting intelligent network growth

12.6.4 REST OF LATIN AMERICA

13 COMPETITIVE LANDSCAPE

13.1 INTRODUCTION

13.2 KEY PLAYER COMPETITIVE STRATEGIES/RIGHT TO WIN, 2023-2026

13.3 MARKET SHARE ANALYSIS, 2025

13.4 REVENUE ANALYSIS, 2021-2025

13.5 BRAND/PRODUCT COMPARISON

13.6 COMPANY EVALUATION MATRIX: KEY PLAYERS, 2025

13.6.1 STARS

13.6.2 EMERGING LEADERS

13.6.3 PERVASIVE PLAYERS

13.6.4 PARTICIPANTS

13.6.5 COMPANY FOOTPRINT: KEY PLAYERS, 2025

13.6.5.1 Company footprint

13.6.5.2 Region footprint

13.6.5.3 Offering footprint

13.6.5.4 Solution footprint

13.6.5.5 Service footprint

13.6.5.6 Network type footprint

13.6.5.7 End user footprint

13.7 COMPANY EVALUATION MATRIX: STARTUPS/SMES, 2025

13.7.1 PROGRESSIVE COMPANIES

13.7.2 RESPONSIVE COMPANIES

13.7.3 DYNAMIC COMPANIES

13.7.4 STARTING BLOCKS

13.7.5 COMPETITIVE BENCHMARKING: STARTUPS/SMES, 2025

13.7.5.1 Detailed list of key startups/SMEs

13.7.5.2 Competitive benchmarking of key startups/SMEs

13.8 COMPANY VALUATION AND FINANCIAL METRICS

13.9 COMPETITIVE SCENARIO

13.9.1 PRODUCT LAUNCHES/ENHANCEMENTS

13.9.2 DEALS

14 COMPANY PROFILES

14.1 MAJOR PLAYERS

14.1.1 CISCO

14.1.1.1 Business overview

14.1.1.2 Products/Solutions/Services offered

14.1.1.3 Recent developments

14.1.1.3.1 Product launches/enhancements

14.1.1.3.2 Deals

14.1.1.4 Analyst's view

14.1.1.4.1 Right to win

14.1.1.4.2 Strategic choices

14.1.1.4.3 Weaknesses and competitive threats

14.1.2 HPE

14.1.2.1 Business overview

14.1.2.2 Products/Solutions/Services offered

14.1.2.3 Recent developments

14.1.2.3.1 Product launches/enhancements

14.1.2.3.2 Deals

14.1.2.4 Analyst's view

14.1.2.4.1 Right to win

14.1.2.4.2 Strategic choices

14.1.2.4.3 Weaknesses and competitive threats

14.1.3 NOKIA

14.1.3.1 Business overview

14.1.3.2 Products/Solutions/Services offered

14.1.3.3 Recent developments

14.1.3.3.1 Product launches/enhancements

14.1.3.3.2 Deals

14.1.3.4 Analyst's view

14.1.3.4.1 Right to win

14.1.3.4.2 Strategic choices

14.1.3.4.3 Weaknesses and competitive threats

14.1.4 HUAWEI

14.1.4.1 Business overview

14.1.4.2 Products/Solutions/Services offered

14.1.4.3 Recent developments

14.1.4.3.1 Product launches/enhancements

14.1.4.3.2 Deals

14.1.4.3.3 Other developments

14.1.4.4 Analyst's view

14.1.4.4.1 Right to win

14.1.4.4.2 Strategic choices

14.1.4.4.3 Weaknesses and competitive threats

14.1.5 ERICSSON

14.1.5.1 Business overview

14.1.5.2 Products/Solutions/Services offered

14.1.5.3 Recent developments

14.1.5.3.1 Product launches/enhancements

14.1.5.3.2 Deals

14.1.5.3.3 Other developments

14.1.5.4 Analyst's view

14.1.5.4.1 Right to win

14.1.5.4.2 Strategic choices

14.1.5.4.3 Weaknesses and competitive threats

14.1.6 ARISTA NETWORKS

14.1.6.1 Business overview

14.1.6.2 Products/Solutions/Services offered

14.1.6.3 Recent developments

14.1.6.3.1 Product launches/enhancements

14.1.6.3.2 Deals

14.1.7 NVIDIA

14.1.7.1 Business overview

14.1.7.2 Products/Solutions/Services offered

14.1.7.3 Recent developments

14.1.7.3.1 Product launches/enhancements

14.1.7.3.2 Deals

14.1.8 DYNATRACE

14.1.8.1 Business overview

14.1.8.2 Products/Solutions/Services offered

14.1.9 IBM

14.1.9.1 Business overview

14.1.9.2 Products/Solutions/Services offered

14.1.9.3 Recent developments

14.1.9.3.1 Product launches/enhancements

14.1.9.3.2 Deals

14.1.10 INFOBLOX

14.1.10.1 Business overview

14.1.10.2 Products/Solutions/Services offered

14.1.10.3 Recent developments

14.1.10.3.1 Product launches/enhancements

14.1.10.3.2 Deals

14.2 OTHER PLAYERS

14.2.1 BROADCOM

14.2.2 FUJITSU

14.2.3 DELL TECHNOLOGIES

14.2.4 NEC

14.2.5 A10 NETWORKS

14.2.6 SCIENCELOGIC

14.2.7 CIENA

14.2.8 EXTREME NETWORKS

14.2.9 EFFICIENTIP

14.2.10 RIVERBED

14.2.11 NETSCOUT

14.2.12 SOLARWINDS

14.2.13 NETBRAIN

14.2.14 MANAGEENGINE

14.2.15 VIAVI

14.3 SMES/STARTUPS

14.3.1 FORWARD NETWORKS

14.3.2 BLUECAT NETWORKS

14.3.3 VERSA NETWORKS

14.3.4 SELECTOR

14.3.5 AVIZ NETWORKS

14.3.6 NILE

14.3.7 NETBOX LABS

14.3.8 CELONA

14.3.9 SHABODI

14.3.10 A5G NETWORKS

15 RESEARCH METHODOLOGY

15.1 RESEARCH DATA

15.1.1 SECONDARY DATA

15.1.2 PRIMARY DATA

15.1.2.1 Primary interviews with experts

15.1.2.2 Breakdown of primary profiles

15.1.2.3 Key data from primary sources

15.1.2.4 Key industry insights

15.2 MARKET BREAKUP AND DATA TRIANGULATION

15.3 MARKET SIZE ESTIMATION

15.3.1 TOP-DOWN APPROACH

15.3.2 BOTTOM-UP APPROACH

15.4 MARKET FORECAST

15.4.1 FACTOR ANALYSIS

15.5 RESEARCH ASSUMPTIONS

15.6 RESEARCH LIMITATIONS

16 APPENDIX

16.1 DISCUSSION GUIDE

16.2 KNOWLEDGESTORE: THE SUBSCRIPTION PORTAL

16.3 CUSTOMIZATION OPTIONS

16.4 RELATED REPORTS

16.5 AUTHOR DETAILS

LIST OF TABLES [419]

LIST OF FIGURES [55]

For more information about this report visit https://www.researchandmarkets.com/r/zezlhp

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